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カワイ ユキコ
KAWAI YUKIKO
河合 由起子 所属 京都産業大学 情報理工学部 情報理工学科 職種 教授 |
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| 言語種別 | 英語 |
| 発行・発表の年月 | 2011 |
| 形態種別 | 研究論文（国際会議プロシーディングス） |
| 査読 | 査読あり |
| 標題 | Sentiment bias detection in support of news credibility judgment |
| 執筆形態 | その他 |
| 掲載誌名 | Proceedings of the Annual Hawaii International Conference on System Sciences |
| 出版社・発行元 | IEEE Computer Society |
| 巻・号・頁 | pp.1-10 |
| 著者・共著者 | Jianwei Zhang,Yukiko Kawai,Shinsuke Nakajima,Yoshifumi Matsumoto,Katsumi Tanaka |
| 概要 | Recently, an increasing number of online news websites have come to provide news browsing and retrieval services. For certain topics, certain news websites may hold sentiment bias, and therefore select and edit information according to their own standpoints before delivering news articles. Lacking conscious awareness of websites' sentiment bias may result in blind obedience to the reported information. We focus on the sentiment aspect of news articles and develop a system which can detect and visualize sentiment tendencies of different websites. Given a topic, the system extracts relevant subtopics and presents sentiment difference between different subtopics. Once a subtopic is specified, sentiment difference between news websites is also provided. The background knowledge of sentiment difference between subtopics and between websites can assist users in judging the news credibility. In particular, the system analyzes four-dimension sentiment, which is more similar to human emotion than conventional positive-negative sentiment. Experimental evaluations show the accuracy of sentiment extraction and subtopic extraction is good, and our observation results show sentiment bias can be detected by the system. |
| DOI | 10.1109/HICSS.2011.369 |
| ISSN | 1530-1605 |
| DBLP ID | conf/hicss/ZhangKNMT11 |
| PermalinkURL | http://dblp.uni-trier.de/db/conf/hicss/hicss2011.html#conf/hicss/ZhangKNMT11 |